With the advent of advertising as a pillar of Internet commerce, there is an acute need for improved means of increasing the value achieved by advertising agencies. Unfortunately, advertisers may attempt to manipulate existing online advertisement placement systems for competitive advantage. Current online advertising placement systems fail to provide incentives for advertisers to declare their private information such as true budget, entry time, exit time, and bid value. Without incentives to provide accurate private information in existing advertising placement systems, advertisers may continue to attempt to manipulate the ad placement systems for competitive advantage.
For instance, an advertiser may attempt to manipulate an ad placement system by timing the entry and exit time to reduce competition with other bidders and thereby lower the price per click for allocated advertisement placements. Or an advertiser may attempt to manipulate an advertising placement system by underbidding competitors, causing competitors to quickly consume their budgets at a high price, and then bidding for clicks at a lower rate without interference from competitors. Or an advertiser may attempt to manipulate an ad placement system by reporting a small budget to gain finer time granularity in pricing control. This may allow an advertiser to attempt to end a campaign before competition arrives or to prevent his budget from being exhausted by competitors engaging in underbidding. Such behavior calculated to manipulate the ad placement systems in any of these ways may additionally cause advertiser churn from budget exhaustion by overbidding.
There is a need to find incentives that may motivate advertisers to honestly report their private information, including valuations, for any possible allocation. Indeed, in assuming that advertisers have a known valuation per click as well as a bounded budget, many authors have suggested algorithms that increase welfare for the search engine. See for example G. Aggarwal, A. Goel and R. Motwani, Truthful Auctions for Pricing Search Keywords, Proceeding of EC'06. Some authors have even suggested mechanisms which do not assume the knowledge of click-through rates (CTRs) but learn them while running the algorithm. See S. Pandey and C. Olston, Handling Advertisements of Unknown Quality in Search Advertising, to appear in the proceedings of NIPS 06. However, the assumption of known valuations is arguably unrealistic. In practice advertisers' values are private information, and hence advertisers might be motivated to act strategically to increase their utility.
What is needed is a system and method for allocating advertisement placement where private information including the valuation may be unknown. Such a system and method should give advertisers an incentive to declare bids with true valuations, accurately declare their budget for an arrival and departure time, accurately learn the CTR for advertisements, and minimize loss of welfare of the advertisers.